Will AI replace Weighers & Measurers?

In part. We think AI will eventually automate a real share of this work, but the transition opens doors for people willing to grow alongside the technology. Our 28.5% AI Resilience Score reflects real pressure. AI-powered vision systems can now automatically weigh, count, and inspect products for defects , and computer vision in warehouses auto-logs inventory data that workers once recorded by hand . The BLS projects employment in this field to decline 6 percent through 2035 , and broader research shows AI is already trimming headcount in manufacturing and office support roles . That is a genuine warning, not noise. What stays human is the judgment layer: calibrating equipment, catching edge cases the algorithm misses, verifying AI-flagged samples, and understanding quality standards. Those skills matter more as automation spreads, not less. The smarter move is to treat this role as a starting point rather than a destination. Workers who get comfortable with the software running the cameras, who understand measurement standards, and who can troubleshoot when automated systems flag something unusual will find paths into quality technician, process control, or inspection engineering roles. The checking part of this job is shrinking. The thinking part is not.

How is AI changing Weighers & Measurers jobs?

If you're worried about robots taking over this job, here's the honest picture: the "checking and measuring" part is being heavily automated, but the "judgment and problem-solving" part still needs people. The biggest shift is AI-powered vision inspection, where cameras and machine-learning models automatically weigh, count, and check products for defects. According to the trade group A3, AI-powered vision inspection is "becoming a practical addition to the modern manufacturing toolkit" , and some deployments can reduce scrap or manual inspection costs by hundreds of thousands of dollars per production line . Quality Magazine notes that organizations are now using AI to "predict equipment failures, identify process variations, automate inspections" — with the goal of shifting from reactive checking to predictive quality management. For measurement itself, NIST researchers are showing that AI models can extend the viability of measurements from noisy, low-contrast images in semiconductor metrology. Recordkeeping is also being augmented: computer vision systems in warehouses now read operations from camera feeds instead of manual scans and counts , auto-logging inventory data.

How fast is AI adoption growing for Weighers & Measurers?

Adoption is moving fast in warehouses and factories but slower in smaller operations. The U.S. Bureau of Labor Statistics projects overall employment of material recording clerks (which includes weighers and checkers) to decline 6 percent from 2025 to 2035 , signaling that automation is quietly reshaping the field. S&P Global's 2026 research shows AI is already trimming headcount in administration and office support, manufacturing, production and customer service roles. The World Economic Forum similarly flags that clerical and secretarial workers are among the fastest-declining roles as digitization spreads. Still, real-world adoption has friction: A3 points out that training targeted inspection models can require 250 to 1,000 labeled images , and many manufacturers start with cautious proof-of-concept projects. The good news for young workers: skills like calibrating equipment, spotting weird edge cases, verifying AI-flagged samples, and understanding standards remain very human. If you build those skills — plus a little comfort with the software running the cameras — you'll be the person AI needs, not the one it replaces.

Not Very Resilient

Last Update: 11/4/2026

AI Resilience Score for Weighers & Measurers:

28.5%

Median Score

Meaningful human contribution

Low

Long-term employer demand

Low

Sustained economic opportunity

Low

Our confidence in this score:

Medium-high

AI Resilience Report forWeighers, Measurers, Checkers, and Samplers, Recordkeeping

$46,380 median salary•4,700 annual openings•SOC Code: 43-5111.00

Weighers, Measurers, Checkers, and Samplers, Recordkeeping are less resilient to AI impacts than most occupations, according to our analysis of 7 sources.

This career is labeled "Not Very Resilient" because the core tasks, weighing, measuring, checking products, and logging records, are exactly the kind of repetitive, rule-based work that AI and computer vision systems are designed to handle. Automated inspection cameras can now spot defects, count items, and record data faster and more accurately than humans, and the Bureau of Labor Statistics projects a 6 percent decline in employment for these roles from 2025 to 2035.

Learn more about how you can thrive in this position

This role is not very resilient

This career is labeled "Not Very Resilient" because the core tasks, weighing, measuring, checking products, and logging records, are exactly the kind of repetitive, rule-based work that AI and computer vision systems are designed to handle. Automated inspection cameras can now spot defects, count items, and record data faster and more accurately than humans, and the Bureau of Labor Statistics projects a 6 percent decline in employment for these roles from 2025 to 2035.

Read full analysis

Analysis of current AI resilience

Weighers & Measurers

Updated quarterly

Your move

How can Weighers & Measurers prepare for AI?

Learn how AI-powered vision inspection systems work, even at a basic level.

The analysis specifically mentions that AI-powered vision inspection cameras and machine-learning models are now automating the weighing, counting, and defect-checking that humans used to do by hand. You do not need to become an engineer, but understanding how these systems work makes you valuable across manufacturing, logistics, quality control, and tech careers. Explore free resources on computer vision basics, and look into how companies train inspection models using labeled images (the analysis notes this requires 250 to 1,000 labeled images per project), because understanding that data-labeling process is a transferable skill that employers across many industries need right now.

Build your "edge case" judgment skills, because AI still struggles with the weird stuff.

The analysis points out that spotting unusual edge cases and verifying AI-flagged samples remain very human strengths, even as routine checking gets automated. Practice sharpening your critical observation and problem-solving skills in any setting you can, whether that is a part-time job, a science class, or a robotics or quality-control club. These judgment skills transfer directly into roles like quality assurance analyst, process improvement specialist, or AI model reviewer, all of which are growing as companies try to manage the friction that comes with rolling out new automation.

Get comfortable with data, recordkeeping software, and basic quality standards.

The analysis highlights that computer vision systems in warehouses now auto-log inventory data from camera feeds, replacing manual scans and counts. That shift means the people who thrive are the ones who can read, question, and work alongside automated data systems rather than just enter data by hand. Take a free course in spreadsheet tools like Excel or Google Sheets, explore introductory database concepts, and look into quality standards organizations like NIST (mentioned in the analysis for its work on measurement from noisy images) to understand how measurement accuracy and standards shape entire industries beyond this one job.

Follow the industries where AI adoption is moving fastest, so you can position yourself ahead of transitions.

The analysis names warehouses, factories, administration, manufacturing, and customer service as areas where AI is already trimming headcount, citing S&P Global and the World Economic Forum. Rather than being surprised by these shifts, make a habit of reading industry news from sources like Quality Magazine or the A3 trade group (both referenced in the analysis) so you understand where automation is heading next. This kind of industry awareness is a career-long skill that helps you spot when it is time to pivot, what new roles are emerging, and which transferable skills (like calibrating equipment or understanding production processes) are still in demand.

Treat every technical skill you build as a bridge to multiple careers, not just one job.

The analysis notes that employment for material recording clerks is projected to decline 6 percent from 2025 to 2035, which is a clear signal that relying on a single occupation is risky. Think of skills like equipment calibration, process variation analysis, and AI system oversight as building blocks that connect to careers in quality engineering, supply chain technology, data operations, and even AI training and auditing. When you learn something new, ask yourself: "Where else could I use this?" That habit of connecting skills across fields is what makes a career resilient no matter how fast technology changes.

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More Career Info

Career: Weighers, Measurers, Checkers, and Samplers, Recordkeeping

They ensure products meet standards by weighing, measuring, and checking them, then recording the results to keep everything accurate and organized.

SOC Code:

43-5111.00•Source: Bureau of Labor Statistics

Parent Careers

Major Group:Office and Administrative Support Occupations

Minor Group:Material Recording, Scheduling, Dispatching, and Distributing Workers

Broad Group:Weighers, Measurers, Checkers, and Samplers, Recordkeeping

Alternate Titles

Fluid Operator · Inventory Specialist · Quality Assurance Inspector (QA Inspector) · Temperature Taker · Cycle Counter · Scale Operator · Supply Clerk

Employment & Wage Data

Median Wage

$46,380

Jobs (2025)

53,600

Growth (2025-35)

-4.8%

Annual Openings

4,700

Education

High school diploma or equivalent

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

82% ResilienceSupplemental

Unload or unpack incoming shipments.

2

80% ResilienceCore Task

Maintain, monitor, and clean work areas, such as recycling collection sites, drop boxes, counters and windows, and areas around scale houses.

3

70% ResilienceCore Task

Collect product samples and prepare them for laboratory analysis or testing.

4

70% ResilienceSupplemental

Transport materials, products, or samples to processing, shipping, or storage areas, manually or using conveyors, pumps, or hand trucks.

5

65% ResilienceCore Task

Collect or prepare measurement, weight, or identification labels and attach them to products.

6

62% ResilienceSupplemental

Fill orders for products and samples, following order tickets, and forward or mail items.

7

60% ResilienceCore Task

Signal or instruct other workers to weigh, move, or check products.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

Not Very Resilient

28.5%

Methodology and Scoring Rationale

AI Resilience Report forWeighers, Measurers, Checkers, and Samplers, Recordkeeping

This role is not very resilient

Weighers & Measurers

How is AI changing Weighers & Measurers jobs?

Sources

How fast is AI adoption growing for Weighers & Measurers?

Sources

Will AI replace Weighers & Measurers?

Sources

How can Weighers & Measurers prepare for AI?

Your Career Starts Here

Latest AI news for Weighers & Measurers

More Career Info

Career: Weighers, Measurers, Checkers, and Samplers, Recordkeeping

Parent Careers

Alternate Titles

Employment & Wage Data

Task-Level AI Resilience Scores

1

2

3

4

5

6

7